Predicting intraurban PM<sub>2.5</sub> concentrations using enhanced machine learning approaches and incorporating human activity patterns.

Ashayeri, Mehdi; Abbasabadi, Narjes; Heidarinejad, Mohammad; Stephens, Brent

Predicting intraurban PM_2.5 concentrations using enhanced machine learning approaches and incorporating human activity patterns.

Ashayeri, Mehdi; Abbasabadi, Narjes; Heidarinejad, Mohammad; Stephens, Brent.

Afiliación

Ashayeri M; College of Architecture, Illinois Institute of Technology, Chicago, IL, USA.
Abbasabadi N; College of Architecture, Illinois Institute of Technology, Chicago, IL, USA.
Heidarinejad M; Department of Civil, Architectural, and Environmental Engineering, Illinois Institute of Technology, Chicago, IL, USA.
Stephens B; Department of Civil, Architectural, and Environmental Engineering, Illinois Institute of Technology, Chicago, IL, USA. Electronic address: brent@iit.edu.

Environ Res ; 196: 110423, 2021 05.

Article en En | MEDLINE | ID: mdl-33157105

Asunto(s)

Contaminantes Atmosféricos; Contaminación del Aire; Contaminantes Atmosféricos/análisis; Contaminación del Aire/análisis; Monitoreo del Ambiente; Actividades Humanas; Humanos; Aprendizaje Automático; Material Particulado/análisis

Palabras clave

Air pollution modeling; Artificial intelligence; Human activity; Outdoor air quality; Statistical prediction model

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos / Contaminación del Aire Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Environ Res Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Países Bajos

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